library(readxl)
ruta_excel <- "C:\\Users\\jdom3\\Desktop\\Datos tesis.xlsx"
Preventivo1df <- read_excel(ruta_excel, sheet = 'Preventivo - Exp 1 vertical')
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
df_100ppm = Preventivo1df|>
group_by(Dia,Area_herida) |>
filter (Tratamiento=="100 ppm")
df_100ppm <- na.omit(df_100ppm)
df_100ppm
## # A tibble: 36 × 4
## # Groups: Dia, Area_herida [35]
## Numero_petalo Tratamiento Dia Area_herida
## <dbl> <chr> <dbl> <dbl>
## 1 32 100 ppm 1 0
## 2 63 100 ppm 1 0.269
## 3 80 100 ppm 1 0.088
## 4 81 100 ppm 1 0.464
## 5 85 100 ppm 1 0
## 6 87 100 ppm 1 0.22
## 7 91 100 ppm 1 0.405
## 8 94 100 ppm 1 0.222
## 9 32 100 ppm 2 0.605
## 10 63 100 ppm 2 0.777
## # ℹ 26 more rows
Boxplot100ppm <- boxplot(df_100ppm$Area_herida ~ df_100ppm$Dia, frame.plot=F)
df_100ppm <- df_100ppm[!(df_100ppm$Area_herida %in% Boxplot100ppm$out),]
df100ppmprom <- df_100ppm %>%
group_by(Dia) %>%
summarise(Area_prom_100ppm = mean(Area_herida))
df_1ppm = Preventivo1df|>
group_by(Dia,Area_herida) |>
filter (Tratamiento=="1 ppm")
df_1ppm <- na.omit(df_1ppm)
df_1ppm
## # A tibble: 33 × 4
## # Groups: Dia, Area_herida [33]
## Numero_petalo Tratamiento Dia Area_herida
## <dbl> <chr> <dbl> <dbl>
## 1 5 1 ppm 1 0.112
## 2 5 1 ppm 2 0.387
## 3 5 1 ppm 3 0.965
## 4 5 1 ppm 4 6.06
## 5 5 1 ppm 5 10.1
## 6 14 1 ppm 1 0
## 7 14 1 ppm 2 0.939
## 8 14 1 ppm 3 3.09
## 9 14 1 ppm 4 6.78
## 10 14 1 ppm 5 12.3
## # ℹ 23 more rows
Boxplot1ppm <- boxplot(df_1ppm$Area_herida ~ df_1ppm$Dia, frame.plot=F)
df_1ppm <- df_1ppm[!(df_1ppm$Area_herida %in% Boxplot1ppm$out),]
df1ppmprom <- df_1ppm %>%
group_by(Dia) %>%
summarise(Area_prom_1ppm = mean(Area_herida))
df_50ppm = Preventivo1df|>
group_by(Dia,Area_herida) |>
filter (Tratamiento=="50 ppm")
df_50ppm <- na.omit(df_50ppm)
df_50ppm
## # A tibble: 41 × 4
## # Groups: Dia, Area_herida [36]
## Numero_petalo Tratamiento Dia Area_herida
## <dbl> <chr> <dbl> <dbl>
## 1 12 50 ppm 1 0
## 2 20 50 ppm 1 0
## 3 37 50 ppm 1 0.128
## 4 47 50 ppm 1 0.536
## 5 49 50 ppm 1 0
## 6 52 50 ppm 1 0
## 7 60 50 ppm 1 0.172
## 8 78 50 ppm 1 0
## 9 95 50 ppm 1 0
## 10 12 50 ppm 2 0.874
## # ℹ 31 more rows
Boxplot50ppm <- boxplot(df_50ppm$Area_herida ~ df_50ppm$Dia, frame.plot=F)
df_50ppm <- df_50ppm[!(df_50ppm$Area_herida %in% Boxplot50ppm$out),]
df50ppmprom <- df_50ppm %>%
group_by(Dia) %>%
summarise(Area_prom_50ppm = mean(Area_herida))
df_Controlcomercial = Preventivo1df|>
group_by(Dia,Area_herida) |>
filter (Tratamiento=="Control comercial")
df_Controlcomercial <- na.omit(df_Controlcomercial)
df_Controlcomercial
## # A tibble: 18 × 4
## # Groups: Dia, Area_herida [17]
## Numero_petalo Tratamiento Dia Area_herida
## <dbl> <chr> <dbl> <dbl>
## 1 10 Control comercial 1 0
## 2 17 Control comercial 1 0.194
## 3 43 Control comercial 1 0.965
## 4 54 Control comercial 1 0
## 5 98 Control comercial 1 0.242
## 6 10 Control comercial 2 1.37
## 7 17 Control comercial 2 1.07
## 8 43 Control comercial 2 3.38
## 9 54 Control comercial 2 2.92
## 10 98 Control comercial 2 2.21
## 11 10 Control comercial 3 5.21
## 12 17 Control comercial 3 2.82
## 13 43 Control comercial 3 7.87
## 14 54 Control comercial 3 10.9
## 15 98 Control comercial 3 9.80
## 16 10 Control comercial 4 11.1
## 17 17 Control comercial 4 8.00
## 18 43 Control comercial 4 10.2
BoxplotControlcomercial <- boxplot(df_Controlcomercial$Area_herida ~ df_Controlcomercial$Dia, frame.plot=F)
df_Controlcomercial <- df_Controlcomercial[!(df_Controlcomercial$Area_herida %in% BoxplotControlcomercial$out),]
dfControlcomercialprom <- df_Controlcomercial %>%
group_by(Dia) %>%
summarise(Area_prom_Controlcomercial = mean(Area_herida))
df_Control = Preventivo1df|>
group_by(Dia,Area_herida) |>
filter (Tratamiento=="Control absoluto\r\n")
df_Control <- na.omit(df_Control)
df_Control
## # A tibble: 40 × 4
## # Groups: Dia, Area_herida [40]
## Numero_petalo Tratamiento Dia Area_herida
## <dbl> <chr> <dbl> <dbl>
## 1 101 "Control absoluto\r\n" 1 0.067
## 2 101 "Control absoluto\r\n" 2 0.182
## 3 101 "Control absoluto\r\n" 3 0.601
## 4 101 "Control absoluto\r\n" 4 2.52
## 5 102 "Control absoluto\r\n" 1 0.053
## 6 102 "Control absoluto\r\n" 2 0.521
## 7 102 "Control absoluto\r\n" 3 1.61
## 8 102 "Control absoluto\r\n" 4 5.65
## 9 105 "Control absoluto\r\n" 1 0.105
## 10 105 "Control absoluto\r\n" 2 0.235
## # ℹ 30 more rows
BoxplotControl <- boxplot(df_Control$Area_herida ~ df_Control$Dia, frame.plot=F)
df_Control <- df_Control[!(df_Control $Area_herida %in% BoxplotControl$out),]
dfControlprom <- df_Control %>%
group_by(Dia) %>%
summarise(Area_prom_Control = mean(Area_herida))
library(agricolae)
library(ggplot2)
df100ppmprom
## # A tibble: 5 × 2
## Dia Area_prom_100ppm
## <dbl> <dbl>
## 1 1 0.209
## 2 2 1.08
## 3 3 2.89
## 4 4 8.01
## 5 5 9.05
audpc100ppm <- (agricolae::audpc(df100ppmprom$Area_prom_100ppm,df100ppmprom$Dia)/5)
Grafico100ppm <- ggplot(df100ppmprom, aes(Dia, Area_prom_100ppm)) + geom_rect(aes(xmin = Dia - 0.5, xmax = Dia + 0.5, ymin = 0, ymax = Area_prom_100ppm),fill = "#1874CD", color = "black", alpha = 0.1 ) + geom_line()+
geom_text(data = data.frame(x = 2, y = 2.5, label = paste('AUDPCS', round(audpc100ppm,2))),
aes(x = x, y = y, label = label),
size = 4, hjust = 1, vjust = 1)+
theme_minimal() + labs(x= 'Día' , y = 'Área promedio afectada', title = '100 ppm')
Grafico100ppm
df100ppmprom$Area_prom_100ppm
## [1] 0.208500 1.084625 2.893000 8.014625 9.047000
audpc1ppm <- (agricolae::audpc(df1ppmprom$Area_prom_1ppm,df1ppmprom$Dia)/5)
Grafico1ppm <- ggplot(df1ppmprom, aes(Dia, Area_prom_1ppm)) + geom_rect(aes(xmin = Dia - 0.5, xmax = Dia + 0.5, ymin = 0, ymax = Area_prom_1ppm),fill = "#1874CD", color = "black", alpha = 0.1 ) + geom_line()+
geom_text(data = data.frame(x = 2, y = 2.5, label = paste("AUDPCS", round(audpc1ppm,2))),
aes(x = x, y = y, label = label),
size = 4, hjust = 1, vjust = 1)+
theme_minimal() + labs(x="Día", y= "Área promedio afectada", title = "1 ppm")
Grafico1ppm
audpc50ppm <- (agricolae::audpc(df50ppmprom$Area_prom_50ppm,df50ppmprom$Dia)/5)
Grafico50ppm <- ggplot(df50ppmprom, aes(Dia, Area_prom_50ppm)) + geom_rect(aes(xmin = Dia - 0.5, xmax = Dia + 0.5, ymin = 0, ymax = Area_prom_50ppm),fill = "#1874CD", color = "black", alpha = 0.1 ) + geom_line()+
geom_text(data = data.frame(x = 2, y = 2.5, label = paste("AUDPCS", round(audpc50ppm,2))),
aes(x = x, y = y, label = label),
size = 4, hjust = 1, vjust = 1)+
theme_minimal() + labs(x="Día", y= "Área promedio afectada", title = "50 ppm")
Grafico50ppm
audpcControlcomercial <- (agricolae::audpc(dfControlcomercialprom$Area_prom_Controlcomercial,dfControlcomercialprom$Dia)/4)
GraficoControlcomercial <- ggplot(dfControlcomercialprom, aes(Dia, Area_prom_Controlcomercial)) + geom_rect(aes(xmin = Dia - 0.5, xmax = Dia + 0.5, ymin = 0, ymax = Area_prom_Controlcomercial),fill = "#1874CD", color = "black", alpha = 0.1 ) + geom_line()+
geom_text(data = data.frame(x = 2, y = 2.5, label = paste("AUDPCS", round(audpcControlcomercial,2))),
aes(x = x, y = y, label = label),
size = 4, hjust = 1, vjust = 1)+
theme_minimal() + labs(x="Día", y= "Área promedio afectada", title = "Control comercial")
GraficoControlcomercial
audpcControl <- (agricolae::audpc(dfControlprom$Area_prom_Control,dfControlprom$Dia )/4)
GraficoControl <- ggplot(dfControlprom, aes(Dia, Area_prom_Control)) + geom_rect(aes(xmin = Dia - 0.5, xmax = Dia + 0.5, ymin = 0, ymax = Area_prom_Control),fill = "#1874CD", color = "black", alpha = 0.1 ) + geom_line()+
geom_text(data = data.frame(x = 2, y = 2.5, label = paste("AUDPCS", round(audpcControl,2))),
aes(x = x, y = y, label = label),
size = 4, hjust = 1, vjust = 1)+
theme_minimal() + labs(x="Día", y= "Área promedio afectada", title = "Control")
GraficoControl
barplotpr1 <- data.frame(
"Tratamiento" = as.factor(c("100 ppm","50 ppm", "1 ppm","Control comercial", "Control" )), "AUDPCS" = c(audpc100ppm,audpc50ppm,audpc1ppm,audpcControlcomercial,audpcControl))
barplotpr1 <- as.data.frame(barplotpr1)
barplotpr1
## Tratamiento AUDPCS
## 1 100 ppm 3.324000
## 2 50 ppm 3.122539
## 3 1 ppm 3.413846
## 4 Control comercial 3.612808
## 5 Control 1.124616
barplotpr1f <-ggplot(barplotpr1, aes(Tratamiento, AUDPCS)) + geom_bar(width = 0.5, stat='identity')
barplotpr1f
library(patchwork)
Comb_plot <- Grafico1ppm+Grafico50ppm+Grafico100ppm+GraficoControlcomercial+GraficoControl+ barplotpr1f
Comb_plot
barplotpr1 <- as.data.frame(barplotpr1)
barplotpr1
## Tratamiento AUDPCS
## 1 100 ppm 3.324000
## 2 50 ppm 3.122539
## 3 1 ppm 3.413846
## 4 Control comercial 3.612808
## 5 Control 1.124616
Tratamientopr1 = as.factor(barplotpr1$Tratamiento)
AUDPCSpr1 = as.vector(barplotpr1$AUDPCS)
ruta_excel <- "C:\\Users\\jdom3\\Desktop\\Datos tesis.xlsx"
Preventivo1df <- read_excel(ruta_excel, sheet = 'Preventivo - Exp 1 vertical')